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          <h1 class="post-title" itemprop="name headline">ConcurrentHashMap</h1>
        

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        <p> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;在多线程环境下，使用 HashMap 可能造成不可预知的错误(插入数据失败，死锁等)。所以在并发的情况下，不能使用HashMap。虽然可以使用HashTable, 但是由于 HashTable 实现线程安全的方式导致效率低下的问题。所以 ConcurrentHashMap 就出现了。<br><a id="more"></a></p>
<h4 id="一、实现原理"><a href="#一、实现原理" class="headerlink" title="一、实现原理"></a>一、实现原理</h4><h5 id="1、-JDK-1-7"><a href="#1、-JDK-1-7" class="headerlink" title="1、 JDK 1.7"></a>1、 JDK 1.7</h5><pre><code>ConcurrentHashMap 采用分段锁的技术，将数据分成一段一段的存储，然后给每一段分配一把锁，当某一个线程占用锁访问某段数据
的时候,他段的数据还是可以被其他线程访问。
下图是 JDK1.7 版本 ConcurrentHashMap 的内部结构图
</code></pre><p><img src="/2018/11/19/2018-11-19-ConcurrentHashMap/ConcurrentHashMap.png" alt="ConcurrentHashMap内部结构"></p>
<pre><code>   从上图中可以看出，ConcurrentHashMap 内部分为了多个 Segment,每一个 Segment 下面都有很多个 HashEntry 数组。
对于一个key,需要经过三次Hash操作，才能最终确定这个元素的位置：
  ①: 对 key 进行第一次的 hash 操作，得到 hash 值 h1，即：h1= hash(key);
  ②: 对 h1 的高几位进行 hash操作，得到 hash 值 h2,即：h2 = hash(h1的高几位)，通过 h2 能够确定元素放在哪个 segment。
  ③：对 h2 进行 hash 操作，得到 hash 值 h3,即： h3 = hash(h2),通过 h3 可以确定元素放在哪个 HashEntry 中。
</code></pre><h5 id="2、-JDK-1-8"><a href="#2、-JDK-1-8" class="headerlink" title="2、 JDK 1.8"></a>2、 JDK 1.8</h5><pre><code>在JDK 1.8中，针对 ConcurrentHashMap 做了许多改进。
①: 取消了 Segment 分段存储的方案，改为直接用  transient volatile Node&lt;K,V&gt;[] table 存储数据，并且采用 table 数组元素
作为锁，从而对每一行数据进行加锁，也就减少了并发冲突的概率。
②：类似与 HashMap,将 原先 **table数组+单向链表** 的数据结构修改为 **table数组+链表+红黑树** 的结构。
③：新增字段 transient volatile CounterCell[] counterCells; 可以方便的计算 HashMap 中所有元素的个数，性能大大优于
jdk1.7中的size()方法。
以下根据 ConcurrentHashMap 的 putVal 方法的实现来具体看看 ConcurrentHashMap 的改进
</code></pre><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">final</span> V <span class="title">putVal</span><span class="params">(K key, V value, <span class="keyword">boolean</span> onlyIfAbsent)</span> </span>&#123;</span><br><span class="line">    <span class="keyword">if</span> (key == <span class="keyword">null</span> || value == <span class="keyword">null</span>) <span class="keyword">throw</span> <span class="keyword">new</span> NullPointerException();</span><br><span class="line">    <span class="keyword">int</span> hash = spread(key.hashCode());</span><br><span class="line">    <span class="keyword">int</span> binCount = <span class="number">0</span>;</span><br><span class="line">    <span class="keyword">for</span> (Node&lt;K,V&gt;[] tab = table;;) &#123;</span><br><span class="line">        Node&lt;K,V&gt; f; <span class="keyword">int</span> n, i, fh;</span><br><span class="line">        <span class="comment">// 如果 哈希桶数组 table 为空，则进行初始化</span></span><br><span class="line">        <span class="keyword">if</span> (tab == <span class="keyword">null</span> || (n = tab.length) == <span class="number">0</span>)</span><br><span class="line">            tab = initTable();</span><br><span class="line">        <span class="keyword">else</span> <span class="keyword">if</span> ((f = tabAt(tab, i = (n - <span class="number">1</span>) &amp; hash)) == <span class="keyword">null</span>) &#123;</span><br><span class="line">        <span class="comment">// 根据 key 的哈希值计算的得到table数组索引 i，如果 tab[i] 为空，直接新建节点 node。</span></span><br><span class="line">        <span class="comment">// 此处需要注意的是：①：此操作是原子操作，②： tab[i] 实际上已经变成了链表或红黑树的首节点</span></span><br><span class="line">            <span class="keyword">if</span> (casTabAt(tab, i, <span class="keyword">null</span>,</span><br><span class="line">                         <span class="keyword">new</span> Node&lt;K,V&gt;(hash, key, value, <span class="keyword">null</span>)))</span><br><span class="line">                <span class="keyword">break</span>;                   <span class="comment">// no lock when adding to empty bin</span></span><br><span class="line">        &#125;</span><br><span class="line">        <span class="keyword">else</span> <span class="keyword">if</span> ((fh = f.hash) == MOVED)</span><br><span class="line">        <span class="comment">// 如果 tab[i] 不为空并且 hash 值为 MOVED(-1),说明该链表正在进行 transfer 操作，此处，会去协助扩容转移，</span></span><br><span class="line">        <span class="comment">// 并返回扩容后的 table</span></span><br><span class="line">            tab = helpTransfer(tab, f);</span><br><span class="line">        <span class="keyword">else</span> &#123;</span><br><span class="line">            V oldVal = <span class="keyword">null</span>;</span><br><span class="line">            <span class="comment">// 以下为第一个改进点，对第一个节点进行加锁，而不是像 1.7 给 segment 加锁，进一步减少并发冲突</span></span><br><span class="line">            <span class="keyword">synchronized</span> (f) &#123;</span><br><span class="line">                <span class="keyword">if</span> (tabAt(tab, i) == f) &#123;</span><br><span class="line">                  <span class="comment">// 进一步判断当前元素是不是应该插入table数组该位置挂载的链表或者红黑树中。</span></span><br><span class="line">                    <span class="keyword">if</span> (fh &gt;= <span class="number">0</span>) &#123;</span><br><span class="line">                        binCount = <span class="number">1</span>;</span><br><span class="line">                        <span class="keyword">for</span> (Node&lt;K,V&gt; e = f;; ++binCount) &#123;</span><br><span class="line">                            K ek;</span><br><span class="line">                            <span class="keyword">if</span> (e.hash == hash &amp;&amp;</span><br><span class="line">                                ((ek = e.key) == key ||</span><br><span class="line">                                 (ek != <span class="keyword">null</span> &amp;&amp; key.equals(ek)))) &#123;</span><br><span class="line">                                   <span class="comment">// 如果在链表中找到值为key的节点e，直接更改旧值。</span></span><br><span class="line">                                oldVal = e.val;</span><br><span class="line">                                <span class="keyword">if</span> (!onlyIfAbsent)</span><br><span class="line">                                    e.val = value;</span><br><span class="line">                                <span class="keyword">break</span>;</span><br><span class="line">                            &#125;</span><br><span class="line">                            Node&lt;K,V&gt; pred = e;</span><br><span class="line">                            <span class="keyword">if</span> ((e = e.next) == <span class="keyword">null</span>) &#123;</span><br><span class="line">                              <span class="comment">// 在链表中没有找到值为key 的节点，则新建一个节点，并直接加入到链表的后边。</span></span><br><span class="line">                                pred.next = <span class="keyword">new</span> Node&lt;K,V&gt;(hash, key,</span><br><span class="line">                                                          value, <span class="keyword">null</span>);</span><br><span class="line">                                <span class="keyword">break</span>;</span><br><span class="line">                            &#125;</span><br><span class="line">                        &#125;</span><br><span class="line">                    &#125;</span><br><span class="line">                    <span class="keyword">else</span> <span class="keyword">if</span> (f <span class="keyword">instanceof</span> TreeBin) &#123;</span><br><span class="line">                      <span class="comment">// 如果首节点是 TreeBin类型，说明是红黑树结构，执行 putTreeVal 操作。</span></span><br><span class="line">                        Node&lt;K,V&gt; p;</span><br><span class="line">                        binCount = <span class="number">2</span>;</span><br><span class="line">                        <span class="keyword">if</span> ((p = ((TreeBin&lt;K,V&gt;)f).putTreeVal(hash, key,</span><br><span class="line">                                                       value)) != <span class="keyword">null</span>) &#123;</span><br><span class="line">                            oldVal = p.val;</span><br><span class="line">                            <span class="keyword">if</span> (!onlyIfAbsent)</span><br><span class="line">                                p.val = value;</span><br><span class="line">                        &#125;</span><br><span class="line">                    &#125;</span><br><span class="line">                &#125;</span><br><span class="line">            &#125;</span><br><span class="line">            <span class="keyword">if</span> (binCount != <span class="number">0</span>) &#123;</span><br><span class="line">                <span class="keyword">if</span> (binCount &gt;= TREEIFY_THRESHOLD)</span><br><span class="line">                <span class="comment">// 如果节点数量超过8，则更改结构为红黑树</span></span><br><span class="line">                    treeifyBin(tab, i);</span><br><span class="line">                <span class="keyword">if</span> (oldVal != <span class="keyword">null</span>)</span><br><span class="line">                    <span class="keyword">return</span> oldVal;</span><br><span class="line">                <span class="keyword">break</span>;</span><br><span class="line">            &#125;</span><br><span class="line">        &#125;</span><br><span class="line">    &#125;</span><br><span class="line">    <span class="comment">// 增加计数， 当然这一步可能会触发扩容操作</span></span><br><span class="line">    addCount(<span class="number">1L</span>, binCount);</span><br><span class="line">    <span class="keyword">return</span> <span class="keyword">null</span>;</span><br><span class="line">  &#125;</span><br></pre></td></tr></table></figure>

      
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